Building crime profiles from public data

Over the past several years, crime in Malta has been on the rise (Formosa, 2017). Crime is a very serious issue and a major problem since it effects society, not only in Malta but every country in the world (Adigun, 2013; Badiora and Afon, 2013). Thus, this study aims to find ways with which public data can be exploited and build crime profiles based on the documents and their entities related. The public data used is online news articles and blogs published by the same websites. With the use of Natural Language Processing techniques articles are filtered out and linked to the crime type or crime types that they are related to. Results show that news online can be biased on what news to report. When comparing the articles reported for the tested crime types some news sources focused to report more crimes then others. The statistics obtained by Formosa, do not reflect the crimes reported. Formosa reported that from the total number of crimes, theft makes up to 51% of all crimes (Formosa, 2017), nevertheless, results showed that in some sources, theft was the least crime reported.

Grantor dc:publisher.institution

University of Malta

Year dc:date.issued

2018

• Data mining
• Crime -- Malta
• Natural language processing (Computer science)
• Crime analysis -- Malta

Statement dc:rights

• info:eu-repo/semantics/restrictedAccess

Language dc:language.iso

en

Repository record dc:identifier.uri

https://www.um.edu.mt/library/oar//handle/123456789/40252

OAI identifier oai:identifier

oai:www.um.edu.mt:123456789/40252